Data management method and system based on sleep quality monitoring
By acquiring information on turning over and the time of initiation, sleep quality assessment information is generated, which solves the problem of poor user experience in traditional sleep monitoring methods and achieves in-depth analysis and improved user experience.
Patent Information
- Application Number
- CN202510877635.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-27
- Publication Date
- 2025-11-21
AI Technical Summary
Existing sleep monitoring methods rely on devices such as smart bracelets, but the lack of in-depth data management and analysis results in a poor user experience.
By acquiring information on the user's turning-over movements and the time of initiation through wearable devices, sleep quality assessment information is generated and sent to a cloud server to enable in-depth analysis of the user's sleep data.
It improves users' understanding of sleep quality, helps identify potential problems, and enhances the user experience.
Smart Images
Figure CN120982972A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the technical field of health management, and more specifically, to a data management method and system based on sleep quality monitoring. Background Technology
[0002] In today's society, with the ever-accelerating pace of life and the significant increase in stress levels, more and more people are experiencing a serious decline in sleep quality. Good sleep is crucial to human health, as it not only directly affects a person's physiological state but also has a profound impact on mental health, work efficiency, and quality of life.
[0003] Currently, traditional sleep monitoring methods mainly rely on wearable devices such as smart bracelets. However, the data management of these devices is usually limited to simply recording basic data such as heart rate, lacking in-depth analysis mechanisms. This makes it difficult for users to gain a deeper understanding of their sleep quality, resulting in a poor user experience, which needs further improvement. Summary of the Invention
[0004] Based on this, embodiments of this application provide a data management method and system based on sleep quality monitoring to solve the problem of poor user experience in the prior art.
[0005] In a first aspect, embodiments of this application provide a data management method based on sleep quality monitoring, the method comprising:
[0006] Based on wearable devices, acquire multiple rolling motion information of the target user and the initiation time information corresponding to each rolling motion information;
[0007] Based on the initiation time information, sleep quality assessment information is generated;
[0008] Send the sleep quality assessment information to the designated cloud server.
[0009] Compared with existing technologies, the beneficial effects are as follows: The data management method based on sleep quality monitoring provided in this application embodiment allows the terminal device to efficiently acquire multiple turning-over movements of the target user and the initiation time information corresponding to each turning-over movement based on wearable devices. Then, based on the initiation time information, it accurately generates sleep quality assessment information and finally sends the sleep quality assessment information to a designated cloud server. This enables in-depth analysis of the target user's sleep data, facilitating a deeper understanding of the user's sleep quality, assisting the user in identifying potential sleep problems, effectively improving the user experience, and to a certain extent solving the current problem of poor user experience.
[0010] Secondly, embodiments of this application provide a data management system based on sleep quality monitoring, the system comprising:
[0011] The rolling motion information acquisition module is used to acquire multiple rolling motion information of the target user and the initiation time information corresponding to each rolling motion information based on the wearable device.
[0012] Sleep quality assessment information generation module: used to generate sleep quality assessment information based on the initiation time information;
[0013] Sleep quality assessment information sending module: used to send the sleep quality assessment information to the designated cloud server.
[0014] Thirdly, embodiments of this application provide a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method described in the first aspect above.
[0015] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method described in the first aspect above.
[0016] It is understood that the beneficial effects of the second to fourth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description
[0017] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below.
[0018] Figure 1 This is a flowchart illustrating a data management method provided in an embodiment of this application;
[0019] Figure 2 This is a flowchart illustrating step S200 in a data management method provided in an embodiment of this application;
[0020] Figure 3 This is a flowchart illustrating the process after step S200 in a data management method provided in an embodiment of this application;
[0021] Figure 4 This is a flowchart illustrating the process after step S207 in a data management method provided in an embodiment of this application;
[0022] Figure 5 This is a flowchart illustrating the process after step S300 in a data management method provided in an embodiment of this application;
[0023] Figure 6This is a block diagram of a data management system provided in one embodiment of this application;
[0024] Figure 7 This is a schematic diagram of a terminal device provided in an embodiment of this application. Detailed Implementation
[0025] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.
[0026] In the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.
[0027] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.
[0028] To illustrate the technical solution described in this application, specific embodiments are provided below.
[0029] Please see Figure 1 , Figure 1 This is a flowchart illustrating the data management method based on sleep quality monitoring provided in this embodiment. In this embodiment, the data management method is executed by a terminal device. It is understood that the types of terminal devices include, but are not limited to, tablet computers, laptops, Ultra-Mobile Personal Computers (UMPCs), netbooks, Personal Digital Assistants (PDAs), etc. This embodiment does not impose any restrictions on the specific type of terminal device.
[0030] Please see Figure 1 The data management method provided in this application includes, but is not limited to, the following steps:
[0031] In S100, based on the wearable device, information on multiple rolling movements of the target user and the initiation time information corresponding to each rolling movement is obtained.
[0032] Specifically, the terminal device can acquire multiple turning-over movements of the target user based on a preset wearable device, as well as the initiation time information corresponding to each turning-over movement. The wearable device can be a smart bracelet or a smartwatch; the turning-over movement information describes the turning-over movements of the target user during sleep; and the initiation time information describes the registration time of the turning-over movement information.
[0033] In S200, sleep quality assessment information is generated based on the initiation time information.
[0034] Specifically, after the terminal device obtains the information on the turning-over action and the initiation time, it can quickly generate sleep quality assessment information based on the initiation time information. This helps users to understand their sleep quality in a deeper and simpler way. The sleep quality assessment information includes high-quality sleep information or low-quality sleep information. High-quality sleep information is used to describe the quality of the target user's current sleep process as high-quality sleep, while low-quality sleep information is used to describe the quality of the target user's current sleep process as low-quality sleep.
[0035] For some possible implementations, please refer to [link to relevant documentation] for accurate generation of sleep quality assessment information. Figure 2 Step S200 includes, but is not limited to, the following steps:
[0036] In S210, the total sleep duration information of the target user is obtained.
[0037] Specifically, the terminal device can first obtain the target user's total sleep duration information, which describes the total duration of the target user's current sleep process.
[0038] In S220, based on preset intervals, the total sleep duration information is divided and processed to generate light sleep cycle information, moderate sleep cycle information, deep sleep cycle information, and REM sleep cycle information.
[0039] Specifically, after the terminal device acquires the total sleep duration information, it can divide the information based on preset intervals to generate light sleep cycle information, moderate sleep cycle information, deep sleep cycle information, and REM sleep cycle information. The specific value of the interval can be predefined by the monitoring personnel. For example, the terminal device can first divide the total sleep duration information into multiple sleep cycles, with each cycle lasting 90 minutes. If the last sleep cycle is less than 90 minutes, the terminal device can omit it. Then, each sleep cycle is divided into light sleep cycle information, moderate sleep cycle information, deep sleep cycle information, and REM sleep cycle information. The light sleep cycle information can be the first 10 minutes of the sleep cycle; the moderate sleep cycle information can be the 10th to 30th minutes; the deep sleep cycle information can be the 30th to 70th minutes; and the REM sleep cycle information can be the 70th to 90th minutes.
[0040] In S230, for deep sleep cycle information and REM sleep cycle information: based on the initiation time information corresponding to any two adjacent turning movements, the turning interval duration information is generated.
[0041] Specifically, after the terminal device generates light sleep cycle information, moderate sleep cycle information, deep sleep cycle information, and REM sleep cycle information, the terminal device can generate turning interval duration information for the initiation time information of any two adjacent turning movements within the deep sleep cycle information, and generate turning interval duration information for the initiation time information of any two adjacent turning movements within the REM sleep cycle information. The turning interval duration information is used to describe the time interval between the initiation time information of two adjacent turning movements.
[0042] It should be noted that the target users may experience frequent tossing and turning due to factors such as discomfort, anxiety, pain, or a poor sleep environment. These factors can all lead to sleep interruptions, resulting in a significant reduction in deep sleep and REM sleep, thereby affecting overall sleep quality.
[0043] In S240, it is determined whether the first interval duration information and the second interval duration information corresponding to the rolling over action information are both greater than the preset rolling over interval duration information.
[0044] Specifically, after the terminal device generates the turning-over interval duration information, the terminal device can determine whether the first interval duration information and the second interval duration information corresponding to the turning-over action information are both greater than the preset turning-over interval duration information, thereby accurately determining whether the target user is turning over frequently. Here, the end time of the first interval duration information is the initiation time information of the turning-over action information, that is, the first interval duration information is the time interval before the turning-over action information; the start time of the second interval duration information is the initiation time information of the turning-over action information, that is, the second interval duration information is the time interval after the turning-over action information.
[0045] In S250, if the first interval duration information and the second interval duration information corresponding to the rolling over action information are both greater than the preset rolling over interval duration information, then the rolling over action information is determined to be reasonable action information; otherwise, abnormal action information is generated.
[0046] Specifically, if both the first and second interval durations corresponding to the rolling over action information are greater than the preset rolling over interval duration, it indicates that the target user's rolling over is a reasonable action, and the terminal device can determine that the rolling over action information is reasonable action information. Otherwise, it indicates that the target user's rolling over is an unreasonable action, and the terminal device can generate abnormal action information, that is, determine that the rolling over action information is abnormal action information.
[0047] In S260, it is determined whether the number of abnormal action information corresponding to the deep sleep cycle information is less than a preset number threshold information, and whether the number of abnormal action information corresponding to the REM sleep cycle information is less than the number threshold information.
[0048] Specifically, after the terminal device determines whether the turning-over action information is reasonable or abnormal, the terminal device can determine whether the number of abnormal action information corresponding to the deep sleep cycle information is less than a preset number threshold information, and whether the number of abnormal action information corresponding to the REM sleep cycle information is less than the number threshold information. The specific value of the number threshold information can be 2 or 3, and the preferred value of the number threshold information is 3.
[0049] In S270, if the number of abnormal action information corresponding to the deep sleep cycle information is less than the preset quantity threshold information, and the number of abnormal action information corresponding to the REM sleep cycle information is less than the quantity threshold information, then the sleep quality assessment information is determined to be high-quality sleep information; otherwise, the sleep quality assessment information is determined to be poor-quality sleep information.
[0050] Specifically, if the number of abnormal movement information corresponding to the deep sleep cycle information is less than the preset threshold information, and the number of abnormal movement information corresponding to the REM sleep cycle information is less than the threshold information, it means that the target user does not frequently turn over, so the terminal device can determine that the sleep quality assessment information is high-quality sleep information; otherwise, it means that the target user frequently turns over, so the terminal device can determine that the sleep quality assessment information is poor-quality sleep information.
[0051] In some possible implementations, poor sleep information includes mild or severe poor sleep information; for users to gain a deeper understanding of their sleep quality, please refer to [link to relevant documentation]. Figure 3 After step S200, the method further includes, but is not limited to, the following steps:
[0052] In S201, for deep sleep cycle information and REM sleep cycle information: obtain the turning amplitude information corresponding to each turning movement information.
[0053] Specifically, the terminal device can acquire the turning amplitude information corresponding to each turning action information in the deep sleep cycle information and the turning amplitude information corresponding to each turning action information in the REM sleep cycle information based on the wearable device. The turning amplitude information is used to describe the range of motion corresponding to the turning action of the target user. For example, when the target user turns from a supine position to a side-lying position, the turning amplitude information is 90 degrees.
[0054] In S202, the mean value of the amplitude is generated based on the average value of multiple turning amplitude information.
[0055] Specifically, after the terminal device obtains the rollover amplitude information, the terminal device can calculate the sum of multiple rollover amplitude information, and then divide the sum by the number of rollover amplitude information to calculate the average value and generate the amplitude average information.
[0056] In S203, amplitude threshold information is generated based on the average amplitude information and the preset adjustment ratio information.
[0057] Specifically, after the terminal device generates the amplitude mean information, it can generate amplitude threshold information based on the amplitude mean information and the preset adjustment ratio information. The specific value of the adjustment ratio information can be predefined by the testing personnel, and the specific value of the adjustment ratio information can be 0.2 or 0.3.
[0058] In S204, the information on each turning amplitude and amplitude threshold is compared to generate information on the number of small turnings and the number of large turnings.
[0059] Specifically, after the terminal device generates the amplitude threshold information, the terminal device can compare each turning amplitude information with the amplitude threshold information to generate small turning number information and large turning number information. The small turning number information is used to describe the number of turning amplitude information corresponding to turning amplitude information less than the amplitude threshold information, and the large turning number information is used to describe the number of turning amplitude information corresponding to turning amplitude information greater than the amplitude threshold information.
[0060] In S205, the information on the number of minor rollovers and the number of major rollovers are compared.
[0061] Specifically, after the terminal device generates information on the number of minor rollovers and the number of major rollovers, the terminal device can compare the information on the number of minor rollovers and the number of major rollovers.
[0062] In S206, if the number of minor turning over is less than or equal to the number of major turning over, then the poor sleep information is determined to be mild poor sleep information.
[0063] Specifically, if the number of minor tossing and turning is less than or equal to the number of major tossing and turning, it indicates that the target user tosses and turns over relatively frequently. Therefore, the terminal device can determine that the poor sleep information is mild poor sleep information.
[0064] In S207, if the number of minor turning over is greater than the number of major turning over, then the poor sleep information is determined to be severely poor sleep information.
[0065] Specifically, if the number of minor tossing and turning is greater than the number of major tossing and turning, it indicates that the target user tosses and turns relatively infrequently, and the terminal device can therefore determine that the poor sleep information is severely poor sleep information.
[0066] In the S300, sleep quality assessment information is sent to a designated cloud server.
[0067] Specifically, after the terminal device generates sleep quality assessment information, it can send the information to a designated cloud server, allowing target users to easily and deeply understand their sleep quality and effectively improve the user experience.
[0068] In some possible implementations, to allow the target user to intuitively understand that the sleep quality was severely poor, please refer to [link to relevant documentation]. Figure 4 After step S207, the method further includes, but is not limited to, the following steps:
[0069] In S208, poor sleep quality information is used to generate poor alert information.
[0070] Specifically, the terminal device can generate a poor sleep quality reminder message based on severely poor sleep information. This poor sleep quality reminder message is used to remind the target user that the sleep quality was seriously poor during that sleep session.
[0071] In S209, a quality alert message is sent to the cloud server.
[0072] Specifically, after the terminal device generates a substandard alert message, it can send the message to the same cloud server.
[0073] In some possible implementations, to help target users intuitively understand the impact of sleep quality on facial skin and promptly seek treatment options, please refer to [link to relevant documentation]. Figure 5 If the sleep quality assessment information indicates poor sleep quality, then after step S200, the method further includes, but is not limited to, the following steps:
[0074] In the S400, in response to a skin detection command initiated by the target user, the real-time facial information of the target user is obtained.
[0075] Specifically, the terminal device can respond to the skin detection command initiated by the target user and obtain the target user's real-time facial information based on a preset high-resolution camera. The high-resolution camera can be built into a smart mirror cabinet, smart bathroom mirror, smart makeup mirror, or smart full-length mirror in the bedroom.
[0076] For example, when a target user who has just woken up sits in front of the smart beauty mirror, the target user can initiate a skin detection command through their corresponding terminal. Then, the terminal device controls the high-resolution camera of the smart beauty mirror to take real-time pictures of the target user's face and obtain the target user's real-time facial information.
[0077] In S410, based on real-time facial information and a preset target detection algorithm, information on the type and location of skin blemishes is generated.
[0078] Specifically, after the terminal device acquires real-time facial information, it can generate skin blemish type information and skin blemish location information based on the real-time facial information and a preset target detection algorithm. The target detection algorithm can be based on R-CNN, Faster R-CNN, Mask R-CNN, or YOLO v10. The skin blemish type information describes the blemishes on the target user's facial skin, such as acne, pigmentation, and dark circles. The skin blemish location information describes the location of the skin blemish type information on the target user's face.
[0079] In S420, the first skin blemish record information is obtained based on a preset historical database.
[0080] Specifically, after the terminal device generates information on the type and location of skin blemishes, the terminal device can obtain first skin blemish record information based on a preset historical database. The first skin blemish record information describes historical facial information sorted in chronological order, and each historical facial information is marked with skin blemish type and location information. The historical facial information describes the target user's real-time facial information in history.
[0081] In S430, the skin blemish record information is updated based on the skin blemish type information and the skin blemish location information to generate a second skin blemish record information.
[0082] Specifically, after the terminal device obtains the first skin blemish record information, it can update the skin blemish record information based on the skin blemish type and location information to generate a second skin blemish record information. This allows the target user to understand their skin changes and intuitively understand the impact of sleep quality on facial skin. The second skin blemish record information is used to describe the updated first skin blemish record information.
[0083] The implementation principle of the data management method based on sleep quality monitoring in this application embodiment is as follows: The terminal device can first quickly obtain multiple turning-over movements information of the target user and the initiation time information corresponding to each turning-over movement information based on the wearable device. Then, based on the initiation time information, it accurately generates sleep quality assessment information. Finally, it sends the sleep quality assessment information to the designated cloud server, thereby realizing in-depth analysis of the target user's sleep data, making it easier for users to understand their own sleep quality and effectively improving the user experience.
[0084] It should be noted that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.
[0085] Embodiments of this application also provide a data management system based on sleep quality monitoring. For ease of explanation, only the parts relevant to this application are shown, such as... Figure 6 As shown, the system 60 includes:
[0086] The rolling motion information acquisition module 61 is used to acquire multiple rolling motion information of the target user and the initiation time information corresponding to each rolling motion based on the wearable device;
[0087] Sleep quality assessment information generation module 62: used to generate sleep quality assessment information based on the initiation time information;
[0088] Sleep quality assessment information sending module 63: Used to send sleep quality assessment information to a designated cloud server.
[0089] Optionally, the sleep quality assessment information includes information on high-quality sleep or poor-quality sleep; the aforementioned sleep quality assessment information generation module 62 includes:
[0090] Total Sleep Duration Information Acquisition Submodule: Used to acquire the total sleep duration information of the target user;
[0091] Sleep cycle information generation submodule: Based on preset intervals, it divides the total sleep duration information and generates light sleep cycle information, moderate sleep cycle information, deep sleep cycle information and REM sleep cycle information.
[0092] The submodule for generating turning interval information is used to generate turning interval information based on the initiation time information of any two adjacent turning actions, targeting deep sleep cycle information and REM sleep cycle information.
[0093] Interval duration information judgment submodule: used to determine whether the first interval duration information and the second interval duration information corresponding to the rolling action information are both greater than the preset rolling interval duration information. The end time of the first interval duration information is the initiation time information of the rolling action information, and the start time of the second interval duration information is the initiation time information of the rolling action information.
[0094] Reasonable action information determination submodule: If the first interval duration information and the second interval duration information corresponding to the rolling action information are both greater than the preset rolling interval duration information, then the rolling action information is determined to be reasonable action information; otherwise, abnormal action information is generated.
[0095] Abnormal Action Information Judgment Submodule: Used to determine whether the number of abnormal action information corresponding to deep sleep cycle information is less than a preset number threshold information, and whether the number of abnormal action information corresponding to REM sleep cycle information is less than a number threshold information.
[0096] The high-quality sleep information determination submodule is used to determine the sleep quality assessment information as high-quality sleep information if the number of abnormal action information corresponding to the deep sleep cycle information is less than a preset threshold information, and the number of abnormal action information corresponding to the REM sleep cycle information is less than the threshold information; otherwise, the sleep quality assessment information is determined as poor-quality sleep information.
[0097] Optionally, poor sleep information includes mild poor sleep information or severe poor sleep information; if the sleep quality assessment information is poor sleep information, then the system 60 also includes:
[0098] The rolling motion amplitude information acquisition module is used to acquire the rolling motion amplitude information corresponding to each rolling motion based on deep sleep cycle information and REM sleep cycle information.
[0099] Amplitude mean information generation module: used to generate amplitude mean information based on the average of multiple turning amplitude information;
[0100] Amplitude threshold information generation module: used to generate amplitude threshold information based on the average amplitude information and the preset adjustment ratio information;
[0101] The rolling over frequency information generation module is used to compare each rolling over amplitude information and amplitude threshold information to generate small rolling over frequency information and large rolling over frequency information. The small rolling over frequency information is used to describe the number of rolling over amplitude information that is less than the amplitude threshold information, and the large rolling over frequency information is used to describe the number of rolling over amplitude information that is greater than the amplitude threshold information.
[0102] Rolling-over frequency comparison module: used to compare the number of minor rolling-overs and the number of major rolling-overs;
[0103] Mild poor sleep quality information determination module: If the number of small turning over is less than or equal to the number of large turning over, then the poor sleep quality information is determined to be mild poor sleep quality information;
[0104] The module for determining severe poor sleep quality information is used to determine poor sleep quality information as severe poor sleep quality if the number of minor turning over is greater than the number of major turning over.
[0105] Optionally, the system 60 also includes:
[0106] Poor quality alert information generation module: Used to generate poor quality alert information based on severely poor sleep information;
[0107] Inferior Quality Alert Message Sending Module: Used to send inferior quality alert messages to the cloud server.
[0108] Optionally, if the sleep quality assessment information indicates poor sleep quality, the system 60 may also include:
[0109] Real-time facial information acquisition module: used to acquire the real-time facial information of the target user in response to the skin detection command initiated by the target user;
[0110] Skin blemish type information generation module: used to generate skin blemish type information and skin blemish location information based on real-time facial information and preset target detection algorithms;
[0111] First Skin Imperfection Record Information Acquisition Module: Used to acquire first skin imperfection record information based on a preset historical database;
[0112] Second skin blemish record information generation module: used to update the skin blemish record information based on the skin blemish type information and skin blemish location information, and generate second skin blemish record information.
[0113] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.
[0114] This application also provides a terminal device, such as... Figure 7 As shown, the terminal device 70 of this embodiment includes: a processor 71, a memory 72, and a computer program 73 stored in the memory 72 and executable on the processor 71. When the processor 71 executes the computer program 73, it implements the steps described in the above-described data management method embodiment, for example... Figure 1 Steps S100 to S300 are shown; or, when processor 71 executes computer program 73, it implements the functions of each module in the above-described device, for example... Figure 6 The functions of modules 61 to 63 are shown.
[0115] The terminal device 70 can be a desktop computer, laptop, handheld computer, cloud server, or other computing device, and includes, but is not limited to, a processor 71 and a memory 72. Those skilled in the art will understand that... Figure 7 This is merely an example of terminal device 70 and does not constitute a limitation on terminal device 70. It may include more or fewer components than shown, or combine certain components, or different components. For example, terminal device 70 may also include input / output devices, network access devices, buses, etc.
[0116] The processor 71 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.; the general-purpose processor can be a microprocessor or any conventional processor, etc.
[0117] The memory 72 can be an internal storage unit of the terminal device 70, such as a hard disk or memory of the terminal device 70. The memory 72 can also be an external storage device of the terminal device 70, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the terminal device 70. Furthermore, the memory 72 can include both internal storage units and external storage devices of the terminal device 70. The memory 72 can also store computer program 73 and other programs and data required by the terminal device 70. The memory 72 can also be used to temporarily store data that has been output or will be output.
[0118] One embodiment of this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium can include any entity or device capable of carrying computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.
[0119] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the methods, principles and structures of this application should be covered within the scope of protection of this application.
Claims
1. A data management method based on sleep quality monitoring, characterized in that, The method includes: Based on wearable devices, acquire multiple rolling motion information of the target user and the initiation time information corresponding to each rolling motion information; Based on the initiation time information, sleep quality assessment information is generated; Send the sleep quality assessment information to the designated cloud server.
2. The method according to claim 1, characterized in that, The sleep quality assessment information includes information on good sleep or poor sleep; the generation of sleep quality assessment information based on the initiation time information includes: Obtain the total sleep duration information of the target user; Based on a preset division interval, the total sleep duration information is divided to generate light sleep cycle information, moderate sleep cycle information, deep sleep cycle information, and rapid eye movement sleep cycle information. For the deep sleep cycle information and the rapid eye movement sleep cycle information: generate turning interval duration information based on the initiation time information corresponding to any two adjacent turning movements; Determine whether the first interval duration information and the second interval duration information corresponding to the rolling action information are both greater than the preset rolling interval duration information, wherein the end time of the first interval duration information is the initiation time information of the rolling action information, and the start time of the second interval duration information is the initiation time information of the rolling action information; If both the first interval duration information and the second interval duration information corresponding to the rolling over action information are greater than the preset rolling over interval duration information, then the rolling over action information is determined to be reasonable action information; otherwise, abnormal action information is generated. Determine whether the number of abnormal action information corresponding to the deep sleep cycle information is less than a preset number threshold information, and whether the number of abnormal action information corresponding to the rapid eye movement sleep cycle information is less than the number threshold information; If the number of abnormal movement information corresponding to the deep sleep cycle information is less than a preset threshold information, and the number of abnormal movement information corresponding to the rapid eye movement sleep cycle information is less than the threshold information, then the sleep quality assessment information is determined to be high-quality sleep information; otherwise, the sleep quality assessment information is determined to be low-quality sleep information.
3. The method according to claim 2, characterized in that, The poor sleep information includes mild poor sleep information or severe poor sleep information; if the sleep quality assessment information is poor sleep information, then after generating the sleep quality assessment information based on the initiation time information, For the deep sleep cycle information and the rapid eye movement sleep cycle information: obtain the turning amplitude information corresponding to each turning movement information; Generate mean amplitude information based on the average of multiple rolling amplitude information; Amplitude threshold information is generated based on the mean amplitude information and the preset adjustment ratio information; By comparing each of the rolling amplitude information and amplitude threshold information, small rolling number information and large rolling number information are generated. The small rolling number information is used to describe the number of rolling amplitude information corresponding to rolling amplitude information less than amplitude threshold information, and the large rolling number information is used to describe the number of rolling amplitude information corresponding to rolling amplitude information greater than amplitude threshold information. Compare the information on the number of minor rollovers and the number of major rollovers; If the number of minor turning over is less than or equal to the number of major turning over, then the poor sleep quality information is determined to be mild poor sleep quality information; If the number of minor turning over is greater than the number of major turning over, then the poor sleep quality information is determined to be severely poor sleep quality information.
4. The method according to claim 3, characterized in that, After determining that the poor sleep quality information is severely poor sleep quality if the number of minor turning over is greater than the number of major turning over, the method further includes: Based on the aforementioned severely poor sleep quality information, a poor sleep quality reminder message is generated; Send the inferior quality alert message to the cloud server.
5. The method according to claim 3, characterized in that, If the sleep quality assessment information is poor sleep information, then after generating the sleep quality assessment information based on the initiation time information, the method further includes: In response to a skin detection command initiated by a target user, the real-time facial information of the target user is obtained; Based on the real-time facial information and the preset target detection algorithm, information on the type and location of skin blemishes is generated. Based on a preset historical database, obtain the first record of skin blemishes; Based on the skin blemish type information and the skin blemish location information, the skin blemish record information is updated to generate a second skin blemish record information.
6. A data management system based on sleep quality monitoring, characterized in that, The system includes: The rolling motion information acquisition module is used to acquire multiple rolling motion information of the target user and the initiation time information corresponding to each rolling motion information based on the wearable device. Sleep quality assessment information generation module: used to generate sleep quality assessment information based on the initiation time information; Sleep quality assessment information sending module: used to send the sleep quality assessment information to the designated cloud server.
7. The system according to claim 6, characterized in that, If the sleep quality assessment information is poor sleep information, then the system includes: Real-time facial information acquisition module: used to acquire the real-time facial information of the target user in response to the skin detection command initiated by the target user; Skin blemish type information generation module: used to generate skin blemish type information and skin blemish location information based on the real-time facial information and the preset target detection algorithm; First Skin Imperfection Record Information Acquisition Module: Used to acquire first skin imperfection record information based on a preset historical database; Second skin blemish record information generation module: used to update the skin blemish record information according to the skin blemish type information and the skin blemish location information, and generate second skin blemish record information.
8. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 5.
9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 5.